(1) Technical Field
The present invention relates to a system for recognizing motion, and more particularly, to motion recognition system that recognizes entity motions to distinguish human motion from animal motion using video streams.
(2) Description of Related Art
An ability to distinguish human motion from animal motion is important in many applications, such as out-door surveillance systems for homeland security and collision avoidance systems for automobile safety. A challenge for such a system is to develop an ability to extract motion features that can characterize human motion and animal motion effectively. One possible approach is to distinguish two-legged motion from four-legged motion. However, to extract the number of legs from each entity in a motion sequence is computationally expensive and requires high quality input images. Additionally, infrared (IR) video sequences obtained outdoors generally cannot deliver the high quality required to do this reliably.
Only a few techniques to distinguish human motion from animal motion using IR video sequences have been disclosed. Most existing techniques focus on the recognition of various types of human activities using video sequences taken in the visual spectrum and are not applicable to IR video sequences. First, most existing techniques require the computation of motion fields that are very difficult to obtain from IR video sequences since IR imagery provides no texture patterns. Second, the existing techniques only work on visual video sequences obtained from artificially controlled environments and lighting conditions. More specifically, the visual video sequences have much better quality than IR video sequences taken from outside scenes. Finally, to distinguish various types of human activities is a different problem than to distinguish human motion from animal motion.
With advances in IR imaging sensors, it is possible to identify various human activities in both daytime and nighttime using IR video streams. Unfortunately, most existing research on identifying human activities has been focused on daytime scenes using visual video streams, which cannot be used at night. Few investigations into recognizing human activities using IR imagery have been reported in the literature, and most existing techniques developed for visual video systems are not applicable for IR video sequences because of the different quality and characters of visual video imagery and IR video imagery. Therefore, it is necessary to develop new techniques for human activity recognition systems using IR video streams.
Thus, a continuing need exists for a system that can distinguish human motion from animal motion using video sequences.